Restricted Maximum Likelihood (REML) is a statistical method used to estimate variance components in linear mixed models, which adjusts for the loss of degrees of freedom due to estimating fixed effects. It is particularly useful in small sample sizes and provides unbiased estimates of variance and covariance parameters by maximizing the likelihood of a transformed set of data that removes the influence of fixed effects.